Soil Organic Matter Content: A Non-linear Control on Microbial Respiration in Soils

Abstract:

Decomposition of soil organic matter (SOM) and the amount of CO₂ respired from soil largely depends on the amount of substrate available to microbes. Soils with high SOM concentrations will have higher respiration rates than soils with low SOM concentrations given similar environmental conditions. It is widely assumed that microbial activity and respiration rates respond linearly to substrate concentrations. This assumption remains however largely untested.

In a lab incubation experiment, we amended a mixture of agricultural soil and sand with increasing amounts of one of three plant residues differing in their C/N ratio (clover 14; rye 23 and wheat straw 110). We used 9 levels of organic carbon (OC) content ranging from 0.25% to 5.7%. The mixtures were then incubated at constant temperature and water contents for 63 days.

Our results show that across substrates CO₂ production increased with increasing OC content following a quadratic function instead of the expected linear one up to 2.2% OC. Above that point CO₂ production leveled off and increased linearly. We hypothesize that the probability that a microbe meets a substrate also increases with increasing amounts of plant residues.

At all substrate concentrations, samples amended with clover had the highest carbon losses, followed by rye and straw. Differences between the three kinds of plant residue might have been caused by their C/N ratios and thus the amount of available N. High amounts of N might have led to an increase in microbial biomass, which could occupy more space and is thus more likely to meet new substrate. Additional analysis of microbial biomass, enzyme activities and N pools will help to understand the mechanism leading to the observed CO₂ patterns.

A non-linear relation of CO₂ production and OC content indicates that spatial separation as an inherent property of SOM content is an important control on decomposition at low OC contents. Knowledge of this controlling effect could be used to enhance N availability in agricultural systems or to improve mitigation strategies for climate change. Finally, implemented in ecosystem models our results will help to improve predictions about microbial limitations and changes in decomposition under a future climate.